1. Field of the Invention
The present invention relates generally to the field of data mining and, more particularly, to methods and systems for mining one or more structured datasets to automatically extract patterns or associations within the data.
2. Description of the Related Art
One of the growing, critical challenges facing the intelligence community is to produce actionable intelligence from massive (and still-increasing) datasets, in a decreasing amount of time. Current analysis tools, such as GALE (Generic Area Limitation Environment) or DCGS (Distributed Common Ground Systems), enable analysts to examine, and confirm or reject, hypotheses they have formed. These confirmatory methods and tools are a necessary part of intelligence analysis; however, they use a trial-and-error based approach that consumes large amounts of time, and they highlight one of the shortcomings of using only the tried-and-true methods of the previous generations of analysts in today's world.
Previous analysis methods were human-centric and, as such, allowed the extraordinary decision capabilities of the mind to be leveraged in analyzing the pertinent, hard-to-come-by intelligence data. With the massive collections of data that occur every day, indeed every hour, in a region of interest, the human mind can only leverage its power on an infinitesimal portion of the collected data. Moreover, it is now an extremely complex challenge to know which are the pertinent data buried in the massive amounts of collected data.
A need therefore exists for an automated, exploratory, data-centric mode of analysis capable of discovering patterns, creating metadata, or simply generating a more concentrated grouping of data to be added to the manual, confirmatory, human-centric mode to facilitate the vast majority of data collected. This data-centric mode of analysis must leverage the processing power of computers to assist the analysts in producing critical actionable intelligence needed to facilitate national security.